Unlocking spectrum for the mobile industry to deliver innovative 5G services across different industry sectors could add $565 billion to global GDP and $152 billion in tax revenue from 2020 to 2034, according to a new report launched today by the GSMA. Next-generation 5G services will improve access to healthcare, education and mobility whilst reducing pollution and increasing safety. However, these outcomes rely on government support for the identification of sufficient millimetre wave (mmWave) spectrum for the mobile industry at the next ITU World Radiocommunication Conference in 2019 (WRC-19).
The report, “Socio-Economic Benefits of 5G Services Provided in mmWave Bands”, is the first to examine and quantify the impact of mmWave spectrum on the overall contribution of 5G networks to society. mmWave spectrum will carry the highest capacity 5G services. It has the ideal characteristics to support very high data transfer rates and ultra-reliable, low latency capabilities, which will support new use cases and deliver the benefits of 5G to consumers and businesses around the world.
“The global mobile ecosystem knows how to make spectrum work to deliver a better future,” said Brett Tarnutzer, Head of Spectrum, GSMA. “Mobile operators have a history of maximising the impact of our spectrum resources and no one else has done more to transform spectrum allocations into services that are changing people’s lives. Planning spectrum is essential to enable the highest 5G performance and government backing for mmWave mobile spectrum at WRC-19 will unlock the greatest value from 5G deployments for their citizens.
“More than 5 billion people already rely on the mobile ecosystem to deliver services that are integral to their daily lives and fundamental to the economic sustainability of the communities they live in. 5G can offer more benefits and a whole new range of services to even more people, but this will not be possible without access to this vital spectrum.”
New Possibilities for Consumers and Industry
mmWave 5G will not only provide consumers with ultra-fast mobile broadband services including immersive entertainment, but will stimulate a host of applications that will enable citizens and businesses to do tomorrow what they can’t do today. These innovations will include enhanced remote healthcare and education, industrial automation, virtual and augmented reality, and many others.
In healthcare, improved telemedicine including tactile internet capabilities, better preventative medicine using always-on remote sensors and wearables, and remote surgery and ‘smart’ instruments will only be made possible because of the speed and latency capabilities enabled by mmWave spectrum.
Next-generation robots, remote object manipulation (controlling machines with precision at distance), drones and other real-time control applications in digitised industrial centres are expected to increase efficiency, reduce costs and improve safety as well as lead to innovations in products and processes.
In autonomous transport, mmWave 5G will enable driverless vehicles to communicate with each other, the cloud and the physical environment continuously to create highly efficient public transport networks. These and many other innovative use cases are expected to deliver 25 per cent of the overall value created by 5G in the future.
Global growth from mmWave
The early lead already being established in 5G in the Asia Pacific and Americas regions are expected to generate the greatest share of GDP attributed to mmWave 5G, at $212 billion and $190 billion respectively. Europe is forecast to have the highest percentage of GDP growth attributable to mmWave of any region, with 2.9 per cent.
However, the advantages are not restricted to early-adopting mobile markets and, as the rest of the world deploys 5G in subsequent years, economies of scale derived from spectrum harmonisation will stimulate even faster growth. Regions such as Sub-Saharan Africa, Central Asia and Latin America and the Caribbean could see growth in GDP contribution from mmWave 5G applications of over 65 per cent per year from 2026 until 2034.
“It is critical for governments to recognise the importance of the mmWave aspects of 5G when making decisions at the upcoming WRC-19. Making the right decisions now on spectrum will be vital to stimulating the rapid growth of economies, especially in developing markets, in the coming decade,” added the GSMA’s Brett Tarnutzer. “mmWave spectrum has the capacity to support the innovative services expected from the highest performance of 5G, and only the mobile ecosystem has the technical expertise and track record in collaboration to deliver them at a price acceptable to consumers and businesses around the world.”
New mmWave bands for mobile are being discussed at WRC-19, and the GSMA recommends supporting the 26 GHz, 40 GHz and 66-71 GHz bands for mobile. Global harmonisation of these bands at WRC-19 will create the greatest economies of scale and make broadband more affordable across the world. Outside the WRC-19 process, 28 GHz is also emerging as an important mmWave band for realising the ultra-high-speed vision for 5G. Commercial services using this band have already been launched in the US and it will also be used for mmWave 5G in countries such as South Korea, Japan, India and Canada.
The report, “Socio-Economic Benefits of 5G Services Provided in mmWave Bands”, which includes details of 5G use cases, value and GDP contribution by sector and geography, can be found here.
Now IBM’s Watson joins IoT revolution in agriculture
Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production
IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.
By 2050, the world will need to feed two billion more people without an increase in arable land . IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.
Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”
New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.
Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.”
The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 . Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.
The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.
Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.
IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.
The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.
 The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”
 Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10
What if Amazon used AI to take on factories?
By ANTONY BOURNE, IFS Global Industry Director for Manufacturing
Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.
At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.
If Amazon did factories
If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.
Manufacturing with knowledge
Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.
In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.
As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.
Knowledge for manufacturing
For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.